【摘要】：內(nèi)燃機(jī)的振動信號是復(fù)雜非平穩(wěn)信號,準(zhǔn)確提取內(nèi)燃機(jī)振動信號中的特征信息進(jìn)行模式識別,是對振動信號進(jìn)行故障診斷的關(guān)鍵�；诮�(jīng)驗(yàn)?zāi)B(tài)分解的維格納時頻分析方法,不但保留了維格納分布的所有優(yōu)良特,而且還避免了交叉項(xiàng)的干擾,能夠有效地提取內(nèi)燃機(jī)振動信號的特征信息;在此基礎(chǔ)之上,針對傳統(tǒng)非負(fù)矩陣分解非正交的基矩陣導(dǎo)致數(shù)據(jù)冗余性較大、影響后續(xù)故障分類準(zhǔn)確率提高的問題,提出采用局部非負(fù)矩陣分解的方法,直接對EMD-WVD時頻圖像的矩陣進(jìn)行分解,計(jì)算用于內(nèi)燃機(jī)故障診斷的特征參數(shù),并利用特征參數(shù)進(jìn)行故障分類。對內(nèi)燃機(jī)4種不同工況的振動信號進(jìn)行實(shí)驗(yàn),證明基于EMD-WVD與局部非負(fù)矩陣分解的方法對內(nèi)燃機(jī)氣門間隙的故障診斷的有效性。
[Abstract]:The vibration signal of internal combustion engine is a complex non-stationary signal. It is the key of fault diagnosis to accurately extract the characteristic information from the vibration signal of internal combustion engine for pattern recognition. The Wigner time-frequency analysis method based on empirical mode decomposition not only preserves all the excellent features of Wigner distribution, but also avoids the interference of crossover terms, and can effectively extract the characteristic information of internal combustion engine vibration signal. On this basis, a local nonnegative matrix decomposition method is proposed to solve the problem that the traditional non-negative matrix decomposition leads to greater data redundancy and affects the accuracy of subsequent fault classification. The matrix of EMD-WVD time-frequency image is decomposed directly, and the characteristic parameters used in internal combustion engine fault diagnosis are calculated, and the fault classification is carried out by using the characteristic parameters. The vibration signals of internal combustion engine under four different working conditions are tested and the results show that the method based on EMD-WVD and local nonnegative matrix decomposition is effective in the diagnosis of valve clearance of internal combustion engine.
【作者單位】： 第二炮兵工程大學(xué)五系;
【基金】：國家自然科學(xué)基金青年基金項(xiàng)目(51405498) 陜西省自然科學(xué)基金項(xiàng)目(2013JQ8023)
【分類號】：TK407
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本文編號：2429217